Results for “data-structure”

Analyze and manipulate crystal structures, compute phase diagrams, and access the Materials Project database using the pymatgen library.

Generate CSV, Markdown, and XLSX spreadsheets from structured tabular data.

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

Profiles datasets automatically to assess data quality, structure, and completeness, generating reports with ydata-profiling, pandera, or manual pandas methods.

Transform raw data into compelling narratives with structured story frameworks, visualization techniques, and presentation templates for executive audiences.

Create clear, effective charts and dashboards from structured data using matplotlib, seaborn, and plotly. Use when the user requests data visualization or provides relevant inputs for this workflow.

Validates NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors using the `tao-daft validate` CLI tool.

Write, optimize, and debug Apache Spark jobs for high-performance distributed data processing, ETL pipelines, and big data workloads.

Create data-driven charts with Vega-Lite and Vega, covering bar, line, scatter, heatmap, area, radar, and word cloud visualizations from structured data arrays.

Creating Excel spreadsheets programmatically with openpyxl — worksheets, data, formulas, charts, formatting, and named ranges. Use when generating financial models, data reports, dashboards, or any structured spreadsheet from data or templates.

Guide through a structured data analysis workflow: define the question, validate data quality, select the appropriate analytical method, and produce decision-ready findings with caveats.

Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling. Use when a dataset is new, its quality is unknown, or the user requests open-ended profiling; use data-analysis instead for a defined hypothesis or decision question.

Organize, query, validate, and convert neuroscience and biomedical data using the Brain Imaging Data Structure (BIDS) standard.

Provides guidance on using Apache Spark RDDs, including creation, transformations, actions, and performance considerations.

Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.

Structured data + RAG. NL2SQL hybrid patterns (text-to-SQL then execute vs embed rows), table embedding strategies (row-level, schema-level, hybrid), semantic layer integration (Cube, dbt metrics), LangChain SQLDatabaseChain, LlamaIndex PandasQueryEngine, safe SQL execution (read-only, sandboxed), schema-aware retrieval. Full PostgreSQL + pgvector hybrid code. USE WHEN: user mentions "tabular RAG", "NL2SQL", "text to SQL", "RAG on tables", "database RAG", "SQL RAG", "semantic layer", "structured data RAG" DO NOT USE FOR: unstructured doc RAG - use `rag-architecture`; metadata filtering only - use `self-querying-retriever`; KG retrieval - use `graph-rag`

Designs and implements big data architectures, processes large-scale datasets with distributed systems, and optimizes data pipelines for throughput using Hadoop, Spark, and cloud platforms.

结构化业务数据分析：附件读取与口径核验、定向筛选、规则/阈值判定、指标异动归因、漏斗/留存/实验分析、经营复盘及可审计报告。当用户提供 Excel、CSV、PDF、图片或多份业务材料，要求查数、判异常、解释变化、比较方案或形成行动建议时使用。Use for evidence-grounded analysis of structured business data, including filtering, rule checks, reconciliation, diagnostics, experiments, and decision reports.

Design reliable, scalable, and maintainable data systems by applying principles from storage engines, replication, partitioning, transactions, and consistency models.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.

Organize, query, validate, and convert neuroscience datasets following the Brain Imaging Data Structure (BIDS) standard, including metadata sidecars and derivatives.

Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.

Structures company knowledge bases for business plan automation, defining a 7-category schema, completeness scoring, and storage layouts for Notion or local Markdown.

Define and enforce data schemas and quality checks using pandera, Great Expectations, or manual assertions, with clear error handling and documentation.

Extracts structured business data from Google Maps search results using the BrowserAct API. Provide search keywords, language, and country filters to get clean, usable business data.

Query and filter Datadog logs from the shell using the Composio CLI, enabling scoped log searches, pivoting across services and environments, and exporting structured JSON for downstream analysis.

Extract public web data via HasData APIs, including search engine results, structured data from ecommerce, travel, jobs, and local business platforms, with support for web scraping, pre-parsed APIs, and async jobs.

Queries 20+ bioinformatics databases from the command line or Python for gene info, sequences, BLAST/BLAT, protein structures, viral data, and expression metrics.